First Steps in DAX Optimization

When you create a Power BI report, you might hit some performance issues when you have a large amount of data, complex data models, or complex DAX expressions in your measures. The first goal of this tutorial is to discover possible bottlenecks in analyzing the execution of DAX calculations using tools such as DAX Studio and VertiPaq Analyzer. You can capture and read essential information from a DAX query plan. With this knowledge, the next step is to evaluate different strategies to improve query performance. During this training, you learn the most common patterns that could have performance issues and possible workarounds to solve them.
The training is delivered as a seminar, and the content is very dense. You can try the same techniques in your notebook during the course, but you should consider taking notes during the seminar and practicing later.
The goal is to optimize the report execution and not the refresh time. Thus, this training only considers the performance of DAX expressions and does not cover refresh operation performance related to M code in Query Editor.
The examples are in Power BI, but you can also apply the concept of this training to Power Pivot, Analysis Services Tabular, and Azure Analysis Services.

Learn the internals of Power BI Learn how to measure performance of semantic models Learn how to optimize DAX